1. Introduction
The family Lebiasinidae, which belongs to the order Characiformes, consists of over 70 valid species of small freshwater fish that are widely distributed across South and Central America, spanning from Costa Rica to Argentina [1]. Lebiasinidae is divided into two subfamilies, Lebiasininae (which includes the genera Derhamia, Lebiasina, and Piabucina) and Pyrrhulininae (which includes the genera Copeina, Copella, Nannostomus, and Pyrrhulina) [2]. The latter represents the most diverse clade, and the genus Nannostomus is the most species-rich genus in the subfamily [2]. Most species in Nannostomus are slender and pencil-shaped, with lengths ranging from 1.5 cm to 7 cm, and are highly popular in the aquarium market under the popular name “pencilfish” [1,3,4]. The global aquarium trade has up to 5300 freshwater fish species available for sale each year, with about 1 billion individuals [5]; of these, species in the order Characiformes account for a certain share [1,4]. Despite its economic importance, there have been incomprehensive reports about its basic biological data, including genetic information [3,6]. Given the wide variety of species, diverse body colors, and limited gene sequence databases, understanding the taxonomy of species in the genus Nannostomus poses a significant challenge [2]; the phylogenetic position of family Lebiasinidae within the order Characiformes could be further refined [7]. The phylogenetic position of Lebiasinidae within the order Characiformes has been a topic of frequent discussion [8,9].
In the realm of animals, the mitochondrial genome (mitogenome) is a small, circular genome, ranging in size from 15 to 18 kb [10,11]. It generally contains 13 protein-coding genes (PCGs), 22 transport RNA (tRNA) genes, 2 ribosomal RNA (rRNA) genes, and 1 control region (CR) [12,13]. The 13 PCGs are NADH dehydrogenase subunit 1 (ND1), NADH dehydrogenase subunit 2 (ND2), Cytochrome c oxidase subunit I (COX1), Cytochrome c oxidase subunit II (COX2), ATP synthase F0 subunit 8 (ATP8), ATP synthase F0 subunit 6 (ATP6), Cytochrome c oxidase subunit III (COX3), NADH dehydrogenase subunit 3 (ND3), NADH dehydrogenase subunit 4L (ND4L), NADH dehydrogenase subunit 4 (ND4), NADH dehydrogenase subunit 5 (ND5), NADH dehydrogenase subunit 6 (ND6), and Cytochrome b (Cytb) (arranged in the common order in the mitogenome of the order Characiformes) [12,13]. The utilization of mitogenomes in molecular identification and phylogenetic analysis is prevalent due to their rapid evolution rate, simple structure, low molecular weight, and maternal inheritance [14,15]. Certain mitochondrial gene fragments, namely 16S rRNA, COX1, and Cytb, have been extensively employed in phylogenetic analyses [16,17]. However, the utilization of partial mitochondrial sequences is constrained by their limited capacity to provide comprehensive information [11]. On the other hand, the complete mitogenome offers a higher level of resolution and sensitivity, making it more suitable for the examination of phylogenetic relationships and species classification [18,19].
With the application of next-generation sequencing technology, there has been a growing number of mitogenomes sequenced in recent years [20]. However, only a limited number of complete mitogenomes are available in the family Lebiasinidae [3,6], and no complete mitogenome is available in the genus Nannostomus. In this study, we present the complete mitogenomes of four Nannostomus species, namely Nannostomus beckfordi, Nannostomus marilynae, Nannostomus marginatus, and Nannostomus unifasciatus. Specifically, the mitochondrial characteristics of these four species, including their gene order, genome size, nucleotide composition, codon usage, and tRNA secondary structure, are comparatively analyzed with other species within the order Characiformes. This study provides new data regarding the phylogeny and classification of Nannostomus pencilfish and the order Characiformes, thus providing a theoretical basis for the economic development of aquarium fish markets.
2. Materials and Methods
2.1. Sample Collection and DNA Extraction
All fish specimens were procured from an aquarium market located in Tianjin, China. Samples of these four fish were identified through morphological and molecular identification, utilizing the resources provided by the WorldFish Center’s FishBase database (
2.2. Mitogenome Sequencing and Assembly
Library construction and sequencing were carried out by Shanghai Personal Biotechnology Co., Ltd. (Shanghai, China) on the NovaSeq X Plus platform (Illumina, CA, USA) following the manufacture’s protocol for 150 bp paired-end reads. The depth of the sequencing was 3×. To generate clean data, low-quality sequences were removed. Clean reads were utilized in the assembly of the complete mitogenomes, using Geneious Prime 2023 using Lebiasina multimaculata (AP006766.1) as a template, and both ends of the final assembly were manually examined for any potential overlap in order to construct the circular mitogenomes. The medium sensitivity/speed option was used for the assembly. Consensus sequences were generated with a 50% base call threshold, obtaining the complete mitogenomes.
2.3. Sequence Analysis
Conservative domains of the mitogenomes were identified using two tools: BLAST CD-Search (
2.4. Phylogenetic Analysis
We constructed a concatenated dataset, consisting of the base sequences of the 13 PCGs from a total of 49 species. This dataset was utilized to investigate the phylogenetic relationships within the order Characiformes. Details of the species included in the analysis can be found in Table 1. Cyprinus carpio was employed as an outgroup in this study. All operations were performed in PhyloSuite software package v1.2.3 [26]. The alignment of the datasets was performed in batches using MAFFT v7.505 software [27]. MACSE was used to optimize alignments using the classic “Needleman–Wunsch” algorithm [28]. ModelFinder was used to partition the codons and determine the best-fit model for the phylogenetic analyses [29]. Unlike the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC) considers the number of samples. When the number of samples is too large, the BIC can effectively prevent the excessive model complexity caused by excessive model precision [30]. The results of the best-fit model are as follows:
Best-fit model of BI according to BIC:
GTR + F + I + G4: ATP6, GTR + F + I + G4: ATP8 + COX2 + ND4L, GTR + F + I + G4: COX1, GTR + F + I + G4: COX3 + ND1, GTR + F + I + G4: Cytb, GTR + F + I + G4: ND2, GTR + F + I + G4: ND3 + ND4 + ND5, GTR + F + I + G4: ND6.
Best-fit model of ML according to BIC:
TIM2 + F + I + G4: ATP6, TIM2 + F + I + I + R4: ATP8 + COX2 + ND4L, TIM2 + F + I + I + R4: COX1, TIM2 + F + I + I + R4: COX3 + ND1, TIM2 + F + R5: Cytb, TIM2 + F + I + I + R4: ND2, GTR + F + I + I + R4: ND3 + ND4 + ND5, TPM2u + F + R4: ND6.
Phylogenetic trees were constructed using Bayesian inference (BI) and maximum likelihood (ML) methods [31,32]. The BI tree was reconstructed using MrBayes 3.2.6 with four Markov chains (three hot chains and one cold chain). Markov chains were run for 1,000,000 generations and were sampled every 100 generations. The consensus trees based on majority rule were assessed by combining the outcomes of duplicated analyses while discarding the first 25% of generations. The ML tree was reconstructed using IQ-TREE with 1000 bootstrap replicates. Phylogenetic trees were visualized and edited using iTOL (
3. Results
3.1. Genome Organization and Composition
The four complete mitogenomes were classically circular, double-stranded molecules, with sizes of 16,690 bp, 16,667 bp, 16,661 bp, and 16,681 bp (Figure 1). Among these species, N. marginatus had the smallest mitogenome, while N. beckfordi had the largest. The mitogenomes of the four fish contained 13 PCGs, 22 tRNAs, 2 rRNAs, and 1 noncoding CR. Nine genes, including eight tRNAs and ND6, were encoded on the minor strand, while the remaining genes were located on the major strand (Table 2).
The nucleotide composition analysis suggested that four mitogenomes were biased toward A and T (Figure 2a). In addition, this AT bias (A+T > G+C) was also evident in PCGs, RNAs, and CRs. CRs exhibited the highest A+T content, while PCGs, tRNAs, and rRNAs displayed an A+T content similar to that of the total mitogenomes (Figure 2a). The results of the skewness analysis indicated that the AT skews of four mitogenomes were all positive, while the GC skews were predominantly negative (Figure 2b). Differing from L. multimaculata in the same family, the GC skews of tRNAs in Nannostomus were all positive. To determine the nucleotide composition of the order Characiformes, the A+T content and AT skew of 48 mitogenomes (including 14 families: Alestidae, Characidae, Chilodontidae, Citharinidae, Curimatidae, Distichodontidae, Erythrinidae, Gasteropelecidae, Hemiodontidae, Hepsetidae, Lebiasinidae, Parodontidae, Prochilodontidae, and Serrasalmidae) were calculated (Table 1 and Figure 3). The 48 Characiformes mitogenomes had a comparable nucleotide composition; the A+T content was always higher than the G+C content in the total genome (52.45~69.97%), PCGs (51.58~65.16%), tRNAs (54.13~60.96%), and rRNAs (51.37~59.71%). The AT skews were almost positive, indicating a higher occurrence of A than T.
Multiple overlaps between adjacent genes were detected (Table 2). Eight gene overlaps were observed in N. beckfordi and N. unifasciatus, nine in N. marginatus, and ten in N. marilynae, all ranging from 1 to 10 bp. The largest overlaps among the four mitogenomes were all located between ATP8 and ATP6.
3.2. Protein-Coding Genes and Codon Usage
The total lengths of the PCGs in Nannostomus were 11,431 bp, 11,433 bp, 11,432 bp, and 11,431 bp, accounting for 68.49% (N. beckfordi) to 68.62% (N. marginatus) of their total mitogenomes, respectively. All PCGs were encoded on the major strand, except for ND6 on the minor strand (Figure 1 and Table 2). Among the 13 PCGs presented in these four mitogenomes, ATP8 exhibited the smallest size at 168 bp, while ND5 displayed the largest size at 1839 bp.
The majority of PCGs in the four mitogenomes start with the ATG codon, with the exception of ND1 in N. marginatus, which starts with the ATT codon, and COX1 in all four mitochondrial genomes, which starts with the GTG codon. The termination codon varied across these PCGs, namely TAA, TAG, AGG, and T. Across all mitogenomes, the frequency of the termination codon TAA was consistently higher than that of the other three termination codons, whereas the occurrence of the termination codon AGG was the lowest. The usage of the initiation codon and termination codon in 48 mitogenomes was calculated (Table 1 and Figure 4). The Characiformes species are relatively conservative in their use of initiation codons, and their preferences were almost consistent with those of the four newly sequenced species, starting with ATG (Figure 4). However, COX1 of the Characiformes species mainly started with GTG. All Characiformes species share the termination codons TAA, TAG, AGG, and T (Figure 4). Specifically, ND1, ATP8, ATP6, COX3, ND4L, and ND5 predominantly employ TAA as the termination codon, while COX1 primarily utilizes AGG as the termination codon. Additionally, ND6 mainly uses TAG as the termination codon, and ND2, COX2, ND3, ND4, and Cytb predominantly use T as the termination codon.
An RSCU analysis was conducted to investigate the codon usage patterns in the four mitogenomes of Nannostomus (Figure 5). The RSCUs of the four mitogenomes exhibited a high degree of similarity. In addition, RSCU analysis revealed a preference for A/T nucleotides at the third codon position, which was consistent with the biased usage of A+T nucleotides evident in the frequencies of codons. The evolutionary pattern of PCGs in Nannostomus was analyzed using Ka/Ks ratios (Figure 6). Apart from that of ND3, the Ka/Ks ratios of the PCGs were lower than 1.
3.3. rRNA, tRNA Genes, and CR
Two rRNAs, 12S rRNA and 16S rRNA, were transcribed from the major strand in the four mitogenomes (Table 2). 12S rRNA was located between tRNA-Phe and tRNA-Val, while 16S rRNA was found between tRNA-Val and tRNA-Leu. The sizes of the 12S rRNA ranged from 953 bp to 956 bp, while the 16S rRNA varied from 1682 bp to 1696 bp in the mitogenomes.
Twenty-two tRNAs (66–76 bp in size) were interspersed in the four mitogenomes altogether, with fourteen from the major strand and eight transcribed from the minor strand (Table 2). The total lengths of the tRNAs were 1563 bp in N. beckfordi, 1559 bp in N. marilynae, 1565 bp in N. marginatus, and 1559 bp in N. unifasciatus, accounting for 9.36%, 9.35%, 9.39%, and 9.35% of their total mitogenomes, respectively.
CR was found between the genes tRNA-Pro and tRNA-Phe in these four mitogenomes. The sizes of CRs in four mitogenomes ranged from 997 bp (N. marginatus) to 1012 bp (N. beckfordi), accounting for 5.98% to 6.06% of the A+T contents in the CRs of the four mitogenomes, exhibiting consistently higher values than PCGs and RNAs, ranging from 69.88% to 72.20% (Figure 2). Lebiasinidae species had CRs of a similar size, but the length of the repeat units and the number of repeats in them were different (Figure 7). The repeat units of CRs were predominantly dimers and, to a lesser extent, trimers.
3.4. Phylogenetic Relationships
A total of 48 species from 15 families of the order Characiformes were included in the phylogenetic analyses. Additionally, one species from the order Cypriniformes (C. carpio) was selected as the outgroup to establish the phylogenetic trees, our aim being to understand the phylogenetic relationships within the order Characiformes (Table 1). The BI and ML trees shared a similar topological structure, with well-supported values for each clade (Figure 8). Four Nannostomus species in this study were clustered together with L. multimaculata of the same family. Within the order Characiformes, the families Citharinidae and Distichodontidae diverged with species in other families early in the evolutionary history of Characiformes fishes.
4. Discussion
The mitogenomes of the four fish contained 13 PCGs, 22 tRNAs, 2 rRNAs, and 1 noncoding CR, which is typical of vertebrates [10,34,35]. The gene orders of the four fish were found to be identical to the common order of Characiformes, which was previously sequenced [13,36,37]. For nucleotide composition, four mitogenomes had an AT bias (A+T > G+C), which is consistent with previous studies [13,38]. The AT skews were almost positive, indicating a higher occurrence of A than T, as has also been observed in other published Teleostei genomes [10,39]. Some PCGs in the four mitogenomes start with unusual codons, such as ATT and GTG. Previous studies have documented the occurrence of atypical initiation codons in Characiformes, such as Astyanax paranae and Hemigrammus armstrongi [13,40]. Most of the gene overlap regions appeared between PCGs and PCGs, with the largest overlaps all located between ATP8 and ATP6, consistent with other fish mitogenomes [41,42,43,44]. Apart from ND3, the Ka/Ks ratios of other PCGs were lower than 1. This suggests that purifying selection might play a predominant role in shaping the evolutionary patterns of PCGs, meaning that, in most cases, selection eliminates the deleterious mutation, and the protein is unchanged [45]. COX1 had the lowest average Ka/Ks value, suggesting that it was under drastic selection pressure and evolved slowly [46].
The mitogenome structure of the order Characiformes is generally conserved [47], with infrequent occurrences of gene rearrangement events. Through an examination of the available mitogenomes of the Characiformes species in GenBank (
The phylogenetic trees also emphasized the unstable relationships within the family Characidae, which was consistent with previous studies [13,49]. Some Characidae species were clustered with species from other genera (Figure 8). In studies on the genus Brycon, some suggest that the genus Brycon should be classified under the family Characidae [50,51], while others suggest it should be classified under the family Bryconidae [52,53]. Studies in recent years have mainly supported the classification of the genus Brycon belonging to the family Bryconidae [54]. In the phylogenetic analyses in this study, the phylogenetic relationship of the genus Brycon with other species in the family Characidae was, indeed, distant. Therefore, our study also supports the inference that the genus Brycon should be classified under the family Bryconidae. It is evident that species that have undergone gene rearrangement were clustered together with species of the same family, although M. sanctaefilomenae did not cluster with other species in the same genus. Previous studies have indicated that phylogenetic trees based on PCGs are more stable and representative than those based on RNAs [13,55,56]. Therefore, the phylogenetic analyses based on PCGs in this study suggest that gene rearrangement would not significantly impact the phylogenetic relationships within the order Characiformes. Although the Characiformes mitogenome is relatively conserved [47], gene rearrangement events have been discovered in many taxa. In addition, there are still a large number of Characiformes species whose complete mitogenomes have not yet been published, and our knowledge on the structure of Characiformes mitogenomes, especially the pattern and underlying mechanisms of gene rearrangements, is far from comprehensive. Therefore, it is necessary to obtain mitogenome data on more species of the order Characiformes. The selection of species from the genus Nannostomus in this study, as well as other species from the Lebiasinidae family in previous studies, was limited, thereby hindering the ability to conduct a comprehensive analysis. Consequently, to enhance our comprehension of the relationships within this family, it would be helpful to incorporate a broader range of species in forthcoming research endeavors.
5. Conclusions
In summary, the four mitogenomes exhibited a typical circular structure, with the overall sizes varying from 16,661 bp to 16,690 bp, containing 13 PCGs, 2 rRNAs, 22 tRNAs, and 1 CR. Nucleotide composition analysis suggested that the mitochondrial sequences were biased towards A and T. The gene order of the four Nannostomus pencilfish was similar to that of other Osteichthyes fish. Phylogenetic analyses support the current classification of the family Lebiasinidae. The phylogenetic analyses in this study suggest that gene rearrangement would not significantly impact the phylogenetic relationships within the order Characiformes. These findings provide new data on the phylogeny and classification of the order Characiformes, thereby establishing a theoretical foundation for the sustainable development of aquarium fish markets.
Conceptualization, H.L.; methodology, W.X.; software, W.X. and K.H.; formal analysis, W.X., J.T. and G.Z.; resources, W.X., J.T. and B.X.; writing—original draft preparation, W.X.; writing—review and editing, H.L., K.H. and T.X.; funding acquisition, W.X. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Nanjing Forestry University, number 2022001.
Not applicable.
DNA sequences: GenBank accession number OR857846 for Nannostomus beckfordi, OR857847 for Nannostomus marilynae, OR857848 for Nannostomus marginatus, and OR857849 for Nannostomus unifasciatus.
The authors declare no conflicts of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Enlarge this image.Figure 1. Mitogenomes of Nannostomus beckfordi (a), Nannostomus marilynae (b), Nannostomus marginatus (c), and Nannostomus unifasciatus (d). Yellow blocks: CR, green blocks: rRNAs, light purple blocks: tRNAs, dark purple blocks: PCGs.
Enlarge this image.Figure 2. Nucleotide composition of various datasets of mitogenomes. Hierarchical clustering of Lebiasinidae species (y-axis) based on the content (a) and skewness (b).
Enlarge this image.Figure 3. A+T content vs. AT-skew in the 48 mitogenomes of the order Characiformes. (a) Total genome; (b) PCGs; (c) tRNAs; (d) rRNAs.
Enlarge this image.Figure 4. Initiation codon (a) and termination codon (b) usage for the mitochondrial genome protein-coding genes of 48 Characiformes species.
Enlarge this image.Figure 5. RSCUs of three species of Nannostomus; the termination codon is not included.
Enlarge this image.Figure 7. The organization of the control region in five Lebiasinidae mitochondrial genomes. The colored ovals indicate the tandem repeats; the remaining regions are shown with green boxes.
Enlarge this image.Figure 8. The BI (a) and ML (b) phylogenetic trees based on the nucleotide datasets for 13 PCGs from the mitogenomes of 49 species, with the common gene order and rearrangement within Characiformes (yellow boxes indicate the events of gene rearrangement).
The mitogenomes of Characiformes and Cypriniformes used in this study.
| Order. | Family | Genus | Species | Size (bp) | Accession No. |
|---|---|---|---|---|---|
| Characiformes | Alestidae | Abramites | Abramites hypselonotus | 16,685 | MW541938.1 |
| Megaleporinus | Megaleporinus elongatus | 16,774 | KU980144.1 | ||
| Megaleporinus obtusidens | 16,682 | KY825191.1 | |||
| Phenacogrammus | Phenacogrammus interruptus | 16,652 | AB054129.1 | ||
| Bryconidae | Brycon | Brycon henni | 16,885 | KP027535.1 | |
| Brycon nattereri | 16,837 | MT428073.1 | |||
| Brycon orbignyanus | 16,802 | KY825192.1 | |||
| Salminus | Salminus brasiliensis | 17,721 | KM245047.1 | ||
| Characidae | Astyanax | Astyanax aeneus | 16,769 | BK013055.1 | |
| Astyanax mexicanus | 16,768 | BK013062.1 | |||
| Hemigrammus | Hemigrammus armstrongi | 16,789 | MW742324.1 | ||
| Hemigrammus bleheri | 17,021 | LC074360.1 | |||
| Hemigrammus erythrozonus | 16,710 | MT484070.1 | |||
| Hyphessobrycon | Hyphessobrycon amapaensis | 17,824 | MW742322.1 | ||
| Hyphessobrycon elachys | 17,224 | MW315747.1 | |||
| Hyphessobrycon flammeus | 16,008 | MW315748.1 | |||
| Hyphessobrycon herbertaxelrodi | 17,417 | MT769327.1 | |||
| Hyphessobrycon pulchripinnis | 17,618 | MW331227.1 | |||
| Moenkhausia | Moenkhausia costae | 15,811 | MW366831.1 | ||
| Moenkhausia sanctaefilomenae | 18,437 | MW407181.1 | |||
| Paracheirodon | Paracheirodon axelrodi | 17,100 | AB898197.1 | ||
| Paracheirodon innesi | 16,962 | KT783482.1 | |||
| Chilodontidae | Chilodus | Chilodus punctatus | 16,869 | AP011984.1 | |
| Citharinidae | Citharinus | Citharinus congicus | 16,453 | AP011985.1 | |
| Curimatidae | Curimata | Curimata mivartii | 16,705 | KP025764.1 | |
| Curimatopsis | Curimatopsis evelynae | 16,779 | AP011988.1 | ||
| Distichodontidae | Distichodus | Distichodus sexfasciatus | 16,555 | AB070242.1 | |
| Erythrinidae | Hoplias | Hoplias intermedius | 16,629 | KU523584.1 | |
| Hoplias malabaricus | 16,638 | AP011992.1 | |||
| Gasteropelecidae | Carnegiella | Carnegiella strigata | 17,852 | AP011983.1 | |
| Hemiodontidae | Hemiodopsis | Hemiodopsis gracilis | 16,731 | AP011990.1 | |
| Hepsetidae | Hepsetus | Hepsetus odoe | 16,803 | AP011991.1 | |
| Lebiasinidae | Lebiasina | Lebiasina multimaculata | 16,899 | AP006766.1 | |
| Nannostomus | Nannostomus beckfordi | 16,690 | OR857846 | ||
| Nannostomus marilynae | 16,667 | OR857847 | |||
| Nannostomus marginatus | 16,661 | OR857848 | |||
| Nannostomus unifasciatus | 16,681 | OR857849 | |||
| Parodontidae | Apareiodon | Apareiodon affinis | 16,679 | AP011998.1 | |
| Prochilodontidae | Ichthyoelephas | Ichthyoelephas longirostris | 16,840 | KP025763.1 | |
| Prochilodus | Prochilodus argenteus | 16,697 | KR014816.1 | ||
| Prochilodus costatus | 16,699 | KR014817.1 | |||
| Prochilodus lineatus | 16,699 | KM245045.1 | |||
| Serrasalmidae | Colossoma | Colossoma macropomum | 16,703 | KP188830.1 | |
| Metynnis | Metynnis hypsauchen | 16,737 | MH358334.1 | ||
| Myloplus | Myloplus rubripinnis | 16,662 | MH358336.1 | ||
| Piaractus | Piaractus brachypomus | 16,722 | KJ993871.2 | ||
| Piaractus mesopotamicus | 16,722 | KM245046.1 | |||
| Pygocentrus | Pygocentrus nattereri | 16,706 | AP012000.1 | ||
| Cypriniformes | Cyprinidae | Cyprinus | Cyprinus carpio | 16,592 | OL693871.1 |
General features of the mitogenomes of Nannostomus beckfordi, Nannostomus marilynae, Nannostomus marginatus, and Nannostomus unifasciatus.
| Gene | Position | Size (bp) | Orientation | Codon | Intergenic Nucleotides | ||
|---|---|---|---|---|---|---|---|
| From | To | Initiation | Termination | ||||
| tRNA-Phe | 1/1/1/1 | 70/70/71/70 | 70/70/7/70 | +/+/+/+ | 0/0/0/0 | ||
| 12S rRNA | 71/71/72/71 | 1026/1025/1024/1024 | 956/955/953/954 | +/+/+/+ | 0/0/0/0 | ||
| tRNA-Val | 1026/1025/1024/1024 | 1097/1096/1095/1095 | 72/72/72/72 | +/+/+/+ | −1/−1/−1/−1 | ||
| 16S rRNA | 1098/1097/1096/1096 | 2793/2786/2777/2785 | 1696/1690/1682/1690 | +/+/+/+ | 0/0/0/0 | ||
| tRNA-Leu | 2796/2789/2779/2788 | 2871/2864/2854/2863 | 76/76/76/76 | +/+/+/+ | 2/2/1/2 | ||
| ND1 | 2872/2865/2852/2864 | 3846/3839/3826/3838 | 975/975/975/975 | +/+/+/+ | ATG/ATG/ATT/ATG | TAG/TAA/TAA/TAA | 0/0/−3/0 |
| tRNA-Ile | 3851/3843/3832/3842 | 3922/3914/3903/3913 | 72/72/72/72 | +/+/+/+ | 4/3/5/3 | ||
| tRNA-Gln | 3921/3913/3902/3912 | 3991/3983/3972/3982 | 71/71/71/71 | −/−/−/− | −2/−2/−2/−2 | ||
| tRNA-Met | 3992/3983/3973/3986 | 4061/4052/4042/4055 | 70/70/70/70 | +/+/+/+ | 0/−1/0/3 | ||
| ND2 | 4062/4053/4043/4056 | 5106/5099/5087/5100 | 1045/1047/1045/1045 | +/+/+/+ | ATG/ATG/ATG/ATG | T/TAG/T/T | 0/0/0/0 |
| tRNA-Trp | 5107/5098/5088/5101 | 5178/5169/5160/5172 | 72/72/73/72 | +/+/+/+ | 0/−2/0/0 | ||
| tRNA-Ala | 5182/5173/5163/5176 | 5250/5241/5231/5244 | 69/69/69/69 | −/−/−/− | 3/3/2/3 | ||
| tRNA-Asn | 5252/5243/5233/5246 | 5324/5315/5305/5318 | 73/73/73/73 | −/−/−/− | 1/1/1/1 | ||
| tRNA-Cys | 5354/5346/5337/5349 | 5420/5411/5402/5414 | 67/66/66/66 | −/−/−/− | 29/30/31/30 | ||
| tRNA-Tyr | 5421/5412/5403/5415 | 5490/5481/5470/5483 | 70/70/68/69 | −/−/−/− | 0/0/0/0 | ||
| COX1 | 5492/5483/5472/5485 | 7048/7039/7028/7041 | 1557/1557/1557/1557 | +/+/+/+ | GTG/GTG/GTG/GTG | AGG/AGG/AGG/AGG | 1/1/1/1 |
| tRNA-Ser | 7040/7031/7020/7033 | 7110/7101/7090/7103 | 71/71/71/71 | −/−/−/− | −9/−9/−9/−9 | ||
| tRNA-Asp | 7115/7106/7096/7108 | 7184/7175/7165/7177 | 70/70/70/70 | +/+/+/+ | 4/4/5/4 | ||
| COX2 | 7198/7189/7180/7192 | 7888/7879/7870/7882 | 691/691/691/691 | +/+/+/+ | ATG/ATG/ATG/ATG | T/T/T/T | 13/13/14/14 |
| tRNA-Lys | 7889/7880/7871/7883 | 7962/7953/7944/7956 | 74/74/74/74 | +/+/+/+ | 0/0/0/0 | ||
| ATP8 | 7964/7955/7946/7958 | 8131/8122/8113/8125 | 168/168/168/168 | +/+/+/+ | ATG/ATG/ATG/ATG | TAA/TAA/TAA/TAA | 1/1/1/1 |
| ATP6 | 8122/8113/8104/8116 | 8805/8796/8787/8799 | 684/684/684/684 | +/+/+/+ | ATG/ATG/ATG/ATG | TAA/TAA/TAA/TAA | −10/−10/−10/−10 |
| COX3 | 8805/8796/8787/8799 | 9590/9581/9572/9584 | 786/786/786/786 | +/+/+/+ | ATG/ATG/ATG/ATG | TAA/TAA/TAA/TAA | −1/−1/−1/−1 |
| tRNA-Gly | 9590/9581/9572/9584 | 9662/9652/9647/9655 | 73/72/76/72 | +/+/+/+ | −1/−1/−1/−1 | ||
| ND3 | 9663/9653/9648/9656 | 10,008/9998/9993/10,001 | 346/346/346/346 | +/+/+/+ | ATG/ATG/ATG/ATG | T/T/T/T | 0/0/0/0 |
| tRNA-Arg | 10,009/9999/9994/10,002 | 10,079/10,067/10,063/10,071 | 71/69/70/70 | +/+/+/+ | 0/0/0/0 | ||
| ND4L | 10,080/10,068/10,064/10,072 | 10,376/10,364/10,360/10,368 | 297/297/297/297 | +/+/+/+ | ATG/ATG/ATG/ATG | TAA/TAA/TAA/TAA | 0/0/0/0 |
| ND4 | 10,370/10,358/10,354/10,362 | 11,750/11,738/11,734/11,742 | 1381/1381/1381/1381 | +/+/+/+ | ATG/ATG/ATG/ATG | T/T/T/T | −7/−7/−7/−7 |
| tRNA-His | 11,752/11,740/11,735/11,744 | 11,821/11,808/11,804/11,813 | 70/69/70/70 | +/+/+/+ | 1/1/0/1 | ||
| tRNA-Ser | 11,822/11,809/11,805/11,814 | 11,889/11,876/11,872/11,881 | 68/68/68/68 | +/+/+/+ | 0/0/0/0 | ||
| tRNA-Leu | 11,891/11,878/11,874/11,883 | 11,963/11,950/11,946/11,955 | 73/73/73/73 | +/+/+/+ | 1/1/1/1 | ||
| ND5 | 11,964/11,951/11,947/11,956 | 13,802/13,789/13,785/13,794 | 1839/1839/1839/1839 | +/+/+/+ | ATG/ATG/ATG/ATG | TAA/TAA/TAA/TAA | 0/0/0/0 |
| ND6 | 13,799/13,786/13,782/13,791 | 14,317/14,304/14,300/14,309 | 519/519/519/519 | −/−/−/− | ATG/ATG/ATG/ATG | TAG/TAA/TAG/TAA | −4/−4/−4/−4 |
| tRNA-Glu | 14,318/14,305/14,301/14,310 | 14,386/14,372/14,369/14,377 | 69/68/69/68 | −/−/−/− | 0/0/0/0 | ||
| Cytb | 14,392/14,378/14,375/14,383 | 15,534/15,520/15,518/15,525 | 1143/1143/1144/1143 | +/+/+/+ | ATG/ATG/ATG/ATG | TAA/TAA/T/TAA | 5/5/5/5 |
| tRNA-Thr | 15,536/15,522/15,519/15,527 | 15,607/15,595/15,592/15,599 | 72/74/74/73 | +/+/+/+ | 1/1/0/1 | ||
| tRNA-Pro | 15,609/15,597/15,596/15,601 | 15,678/15,666/15,664/15,670 | 70/70/69/70 | −/−/−/− | 1/1/3/1 | ||
| CR | 15,679/15,667/15,665/15,671 | 16,690/16,667/16,661/16,681 | 1012/1001/997/1011 | 0/0/0/0 | |||
References
1. Benzaquem, D.C.; Oliveira, C.; Batista, J.d.S.; Zuanon, J.; Porto, J.I.R. DNA Barcoding in Pencilfishes (Lebiasinidae: Nannostomus) Reveals Cryptic Diversity across the Brazilian Amazon. PLoS ONE; 2015; 10, e0112217. [DOI: https://dx.doi.org/10.1371/journal.pone.0112217] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25658694]
2. Sember, A.; de Oliveira, E.A.; Ráb, P.; Bertollo, L.A.C.; de Freitas, N.L.; Viana, P.F.; Yano, C.F.; Hatanaka, T.; Marinho, M.M.F.; de Moraes, R.L.R. et al. Centric Fusions behind the Karyotype Evolution of Neotropical Nannostomus Pencilfishes (Characiforme, Lebiasinidae): First Insights from a Molecular Cytogenetic Perspective. Genes; 2020; 11, 91. [DOI: https://dx.doi.org/10.3390/genes11010091] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31941136]
3. Beheregaray, L.B.; Schwartz, T.S.; Möller, L.M.; Call, D.; Chao, N.L.; Caccone, A. A set of microsatellite DNA markers for the one-lined pencilfish Nannostomus unifasciatus, an Amazonian flooded forest fish. Mol. Ecol. Notes; 2004; 4, pp. 333-335. [DOI: https://dx.doi.org/10.1111/j.1471-8286.2004.00687.x]
4. Terencio, M.L.; Schneider, C.H.; Porto, J.I.R. Molecular signature of the D-loop in the brown pencilfish Nannostomus eques (Characiformes, Lebiasinidae) reveals at least two evolutionary units in the Rio Negro basin, Brazil. J. Fish Biol.; 2012; 81, pp. 110-124. [DOI: https://dx.doi.org/10.1111/j.1095-8649.2012.03320.x] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22747807]
5. Magalhães, A.L.B.; Daga, V.S.; Bezerra, L.A.V.; Vitule, J.R.S.; Jacobi, C.M.; Silva, L.G.M. All the colors of the world: Biotic homogenization-differentiation dynamics of freshwater fish communities on demand of the Brazilian aquarium trade. Hydrobiologia; 2020; 847, pp. 3897-3915. [DOI: https://dx.doi.org/10.1007/s10750-020-04307-w]
6. Meng, F.; Huang, Y.; Liu, B.; Zhu, K.; Zhang, J.; Jing, F.; Xia, L.; Liu, Y. The complete mitochondrial genome of Lebiasina astrigata (Characiformes: Lebiasinida) and phylogenetic studies of Characiformes. Mitochondrial DNA Part B; 2019; 4, pp. 579-580. [DOI: https://dx.doi.org/10.1080/23802359.2018.1558124]
7. Sassi, F.d.M.C.; Hatanaka, T.; de Moraes, R.L.R.; Toma, G.A.; de Oliveira, E.A.; Liehr, T.; Rab, P.; Bertollo, L.A.C.; Viana, P.F.; Feldberg, E. et al. An Insight into the Chromosomal Evolution of Lebiasinidae (Teleostei, Characiformes). Genes; 2020; 11, 365. [DOI: https://dx.doi.org/10.3390/genes11040365]
8. Calcagnotto, D.; Schaefer, S.A.; DeSalle, R. Relationships among characiform fishes inferred from analysis of nuclear and mitochondrial gene sequences. Mol. Phylogenetics Evol.; 2005; 36, pp. 135-153. [DOI: https://dx.doi.org/10.1016/j.ympev.2005.01.004] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/15904862]
9. de Pinna, M.; Zuanon, J.; Py-Daniel, L.R.; Petry, P. A new family of neotropical freshwater fishes from deep fossorial Amazonian habitat, with a reappraisal of morphological characiform phylogeny (Teleostei: Ostariophysi). Zool. J. Linn. Soc.; 2018; 182, pp. 76-106. [DOI: https://dx.doi.org/10.1093/zoolinnean/zlx028]
10. Xu, W.; Lin, S.; Liu, H. Mitochondrial genomes of five Hyphessobrycon tetras and their phylogenetic implications. Ecol. Evol.; 2021; 11, pp. 12754-12764. [DOI: https://dx.doi.org/10.1002/ece3.8019]
11. Wang, J.; Xu, W.; Liu, Y.; Bai, Y.; Liu, H. Comparative mitochondrial genomics and phylogenetics for species of the snakehead genus Channa Scopoli, 1777 (Perciformes: Channidae). Gene; 2023; 857, 147186. [DOI: https://dx.doi.org/10.1016/j.gene.2023.147186]
12. Boore, J.L. Animal mitochondrial genomes. Nucleic Acids Res.; 1999; 27, pp. 1767-1780. [DOI: https://dx.doi.org/10.1093/nar/27.8.1767]
13. Xu, W.; Wang, J.; Xu, R.; Jiang, H.; Ding, J.; Wu, H.; Wu, Y.; Liu, H. Comparative mitochondrial genomics of tetras: Insights into phylogenetic relationships in Characidae. Biologia; 2022; 77, pp. 2905-2914. [DOI: https://dx.doi.org/10.1007/s11756-022-01195-4]
14. Chang, Y.-S.; Huang, F.-L.; Lo, T.-B. The complete nucleotide sequence and gene organization of carp (Cyprinus carpio) mitochondrial genome. J. Mol. Evol.; 1994; 38, pp. 138-155. [DOI: https://dx.doi.org/10.1007/bf00166161] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/8169959]
15. Zhu, H.-F.; Wang, Z.-Y.; Wang, Z.-L.; Yu, X.-P. Complete mitochodrial genome of the crab spider Ebrechtella tricuspidata (Araneae: Thomisidae): A novel tRNA rearrangement and phylogenetic implications for Araneae. Genomics; 2019; 111, pp. 1266-1273. [DOI: https://dx.doi.org/10.1016/j.ygeno.2018.08.006]
16. Zhu, S.-R.; Fu, J.-J.; Wang, Q.; Li, J.-L. Identification of Channa species using the partial cytochrome c oxidase subunit I (COI) gene as a DNA barcoding marker. Biochem. Syst. Ecol.; 2013; 51, pp. 117-122. [DOI: https://dx.doi.org/10.1016/j.bse.2013.08.011]
17. Serrao, N.R.; Steinke, D.; Hanner, R.H. Calibrating Snakehead Diversity with DNA Barcodes: Expanding Taxonomic Coverage to Enable Identification of Potential and Established Invasive Species. PLoS ONE; 2014; 9, e99546. [DOI: https://dx.doi.org/10.1371/journal.pone.0099546]
18. Powell, A.F.; Barker, F.K.; Lanyon, S.M. Empirical evaluation of partitioning schemes for phylogenetic analyses of mitogenomic data: An avian case study. Mol. Phylogenet. Evol.; 2013; 66, pp. 69-79. [DOI: https://dx.doi.org/10.1016/j.ympev.2012.09.006] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23000817]
19. Chandhini, S.; Vargheese, S.; Philip, S.; Kumar, V.J.R. Deciphering the mitochondrial genome of Malabar snakehead, Channa diplogramma (Teleostei; Channidae). Biologia; 2020; 75, pp. 741-748. [DOI: https://dx.doi.org/10.2478/s11756-019-00385-x]
20. Hu, Y.; Xing, W.; Hu, Z.; Liu, G. Phylogenetic Analysis and Substitution Rate Estimation of Colonial Volvocine Algae Based on Mitochondrial Genomes. Genes; 2020; 11, 115. [DOI: https://dx.doi.org/10.3390/genes11010115]
21. Casal, C.M.V. Global Documentation of Fish Introductions: The Growing Crisis and Recommendations for Action. Biol. Invasions; 2006; 8, pp. 3-11. [DOI: https://dx.doi.org/10.1007/s10530-005-0231-3]
22. Perna, N.T.; Kocher, T.D. Patterns of nucleotide composition at fourfold degenerate sites of animal mitochondrial genomes. J. Mol. Evol.; 1995; 41, pp. 353-358. [DOI: https://dx.doi.org/10.1007/bf01215182]
23. Diao, C.; Xi, Y.; Xiao, T. Identification and analysis of key genes in osteosarcoma using bioinformatics. Oncol. Lett.; 2018; 15, pp. 2789-2794. [DOI: https://dx.doi.org/10.3892/ol.2017.7649]
24. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol. Biol. Evol.; 2018; 35, pp. 1547-1549. [DOI: https://dx.doi.org/10.1093/molbev/msy096]
25. Lowe, T.M.; Eddy, S.R. tRNAscan-SE: A Program for Improved Detection of Transfer RNA Genes in Genomic Sequence. Nucleic Acids Res.; 1997; 25, pp. 955-964. [DOI: https://dx.doi.org/10.1093/nar/25.5.955] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/9023104]
26. Zhang, D.; Gao, F.; Jakovlic, I.; Zou, H.; Zhang, J.; Li, W.X.; Wang, G.T. PhyloSuite: An integrated and scalable desktop platform for streamlined molecular sequence data management and evolutionary phylogenetics studies. Mol. Ecol. Resour.; 2020; 20, pp. 348-355. [DOI: https://dx.doi.org/10.1111/1755-0998.13096]
27. Katoh, K.; Standley, D.M. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol. Biol. Evol.; 2013; 30, pp. 772-780. [DOI: https://dx.doi.org/10.1093/molbev/mst010] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23329690]
28. Ranwez, V.; Douzery, E.J.P.; Cambon, C.; Chantret, N.; Delsuc, F. MACSE v2: Toolkit for the Alignment of Coding Sequences Accounting for Frameshifts and Stop Codons. Mol. Biol. Evol.; 2018; 35, pp. 2582-2584. [DOI: https://dx.doi.org/10.1093/molbev/msy159]
29. Kalyaanamoorthy, S.; Minh, B.Q.; Wong, T.K.F.; Von Haeseler, A.; Jermiin, L.S. ModelFinder: Fast model selection for accurate phylogenetic estimates. Nat. Methods; 2017; 14, pp. 587-589. [DOI: https://dx.doi.org/10.1038/nmeth.4285]
30. Liddle, A.R. Information criteria for astrophysical model selection. Mon. Not. R. Astron. Soc. Lett.; 2007; 377, pp. L74-L78. [DOI: https://dx.doi.org/10.1111/j.1745-3933.2007.00306.x]
31. Yang, Z. Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: Approximate methods. J. Mol. Evol.; 1994; 39, pp. 306-314. [DOI: https://dx.doi.org/10.1007/bf00160154] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/7932792]
32. Huelsenbeck, J.P.; Ronquist, F. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics; 2001; 17, pp. 754-755. [DOI: https://dx.doi.org/10.1093/bioinformatics/17.8.754] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/11524383]
33. Zhou, T.; Xu, K.; Zhao, F.; Liu, W.; Li, L.; Hua, Z.; Zhou, X. itol.toolkit accelerates working with iTOL (Interactive Tree of Life) by an automated generation of annotation files. Bioinformatics; 2023; 39, btad339. [DOI: https://dx.doi.org/10.1093/bioinformatics/btad339] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37225402]
34. Montaña-Lozano, P.; Moreno-Carmona, M.; Ochoa-Capera, M.; Medina, N.S.; Boore, J.L.; Prada, C.F. Comparative genomic analysis of vertebrate mitochondrial reveals a differential of rearrangements rate between taxonomic class. Sci. Rep.; 2022; 12, 5479. [DOI: https://dx.doi.org/10.1038/s41598-022-09512-2] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35361853]
35. Jia, Y.; Qiu, G.; Cao, C.; Wang, X.; Jiang, L.; Zhang, T.; Geng, Z.; Jin, S. Mitochondrial genome and phylogenetic analysis of Chaohu duck. Gene; 2023; 851, 147018. [DOI: https://dx.doi.org/10.1016/j.gene.2022.147018] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36349575]
36. Pasa, R.; Menegídio, F.B.; Rodrigues-Oliveira, I.H.; da Silva, I.B.; de Campos, M.L.C.B.; Rocha-Reis, D.A.; Heslop-Harrison, J.S.; Schwarzacher, T.; Kavalco, K.F. Ten Complete Mitochondrial Genomes of Gymnocharacini (Stethaprioninae, Characiformes). Insights Into Evolutionary Relationships and a Repetitive Element in the Control Region (D-loop). Front. Ecol. Evol.; 2021; 9, 650783. [DOI: https://dx.doi.org/10.3389/fevo.2021.650783]
37. Zhu, Q.; Luo, S.; Pan, S.; Su, X.; Liu, Z.; Chen, J. Complete mitogenome of Gymnocorymbus ternetzi (Characiformes: Characidae: Gymnocorymbus) and phylogenetic implications. Mitochondrial DNA Part B; 2022; 7, pp. 58-59. [DOI: https://dx.doi.org/10.1080/23802359.2021.2008844]
38. Liu, H.; Sun, C.; Zhu, Y.; Li, Y.; Wei, Y.; Ruan, H. Mitochondrial genomes of four American characins and phylogenetic relationships within the family Characidae (Teleostei: Characiformes). Gene; 2020; 762, 145041. [DOI: https://dx.doi.org/10.1016/j.gene.2020.145041] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32777523]
39. Wang, J.; Tai, J.; Zhang, W.; He, K.; Lan, H.; Liu, H. Comparison of seven complete mitochondrial genomes from Lamprologus and Neolamprologus (Chordata, Teleostei, Perciformes) and the phylogenetic implications for Cichlidae. ZooKeys; 2023; 1184, pp. 115-132. [DOI: https://dx.doi.org/10.3897/zookeys.1184.107091]
40. Silva, D.M.Z.d.A.; Utsunomia, R.; Ruiz-Ruano, F.J.; Oliveira, C.; Foresti, F. The complete mitochondrial genome sequence of Astyanax paranae (Teleostei: Characiformes). Mitochondrial DNA Part B; 2016; 1, pp. 586-587. [DOI: https://dx.doi.org/10.1080/23802359.2016.1222251]
41. Kundu, S.; Kang, H.-E.; Kim, A.R.; Lee, S.R.; Kim, E.-B.; Amin, M.H.F.; Andriyono, S.; Kim, H.-W.; Kang, K. Mitogenomic Characterization and Phylogenetic Placement of African Hind, Cephalopholis taeniops: Shedding Light on the Evolution of Groupers (Serranidae: Epinephelinae). Int. J. Mol. Sci.; 2024; 25, 1822. [DOI: https://dx.doi.org/10.3390/ijms25031822] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38339100]
42. Bai, Y.; Yang, K.; Ye, L.; Gao, X. Complete Mitogenome and Phylogenetic Analyses of Galerita orientalis Schmidt-Goebel, 1846 (Insecta: Coleoptera: Carabidae: Galeritini). Genes; 2022; 13, 2199. [DOI: https://dx.doi.org/10.3390/genes13122199] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36553466]
43. Li, Y.; Yi, H.; Zhu, Y. Novel insights into adaptive evolution based on the unusual AT-skew in Acheilognathus gracilis mitogenome and phylogenetic relationships of bitterling. Gene; 2024; 902, 148154. [DOI: https://dx.doi.org/10.1016/j.gene.2024.148154] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38218382]
44. Yang, M.; Yang, Z.; Liu, C.; Lee, X.; Zhu, K. Characterization of the Complete Mitochondrial Genome of the Spotted Catfish Arius maculatus (Thunberg, 1792) and Its Phylogenetic Implications. Genes; 2022; 13, 2128. [DOI: https://dx.doi.org/10.3390/genes13112128] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36421803]
45. Hurst, L.D. The Ka/Ks ratio: Diagnosing the form of sequence evolution. Trends Genet.; 2002; 18, pp. 486-487. [DOI: https://dx.doi.org/10.1016/s0168-9525(02)02722-1]
46. Hassanin, A.; Léger, N.; Deutsch, J. Evidence for Multiple Reversals of Asymmetric Mutational Constraints during the Evolution of the Mitochondrial Genome of Metazoa, and Consequences for Phylogenetic Inferences. Syst. Biol.; 2005; 54, pp. 277-298. [DOI: https://dx.doi.org/10.1080/10635150590947843] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16021696]
47. Xu, W.; Ding, J.; Lin, S.; Xu, R.; Liu, H. Comparative mitogenomes of three species in Moenkhausia: Rare irregular gene rearrangement within Characidae. Int. J. Biol. Macromol.; 2021; 183, pp. 1079-1086. [DOI: https://dx.doi.org/10.1016/j.ijbiomac.2021.05.049]
48. Padhi, A. Geographic variation within a tandemly repeated mitochondrial DNA D-loop region of a North American freshwater fish, Pylodictis olivaris. Gene; 2014; 538, pp. 63-68. [DOI: https://dx.doi.org/10.1016/j.gene.2014.01.020] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24440244]
49. Mirande, J.M. Morphology, molecules and the phylogeny of Characidae (Teleostei, Characiformes). Cladistics; 2019; 35, pp. 282-300. [DOI: https://dx.doi.org/10.1111/cla.12345]
50. Lima, F.C.; Albrecht, M.P.; Pavanelli, C.S.; Vono, V. Threatened fishes of the world: Brycon nattereri Günther, 1864 (Characidae). Environ. Biol. Fishes; 2008; 83, pp. 207-208. [DOI: https://dx.doi.org/10.1007/s10641-007-9319-1]
51. de Siqueira-Silva, D.H.; Silva, A.P.d.S.; Costa, R.d.S.; Senhorini, J.A.; Ninhaus-Silveira, A.; Veríssimo-Silveira, R. Preliminary study on testicular germ cell isolation and transplantation in an endangered endemic species Brycon orbignyanus (Characiformes: Characidae). Fish Physiol. Biochem.; 2021; 47, pp. 767-776. [DOI: https://dx.doi.org/10.1007/s10695-019-00631-8] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30937624]
52. Travenzoli, N.M.; Silva, P.C.; Santos, U.; Zanuncio, J.C.; Oliveira, C.; Dergam, J.A. Cytogenetic and Molecular Data Demonstrate that the Bryconinae (Ostariophysi, Bryconidae) Species from Southeastern Brazil Form a Phylogenetic and Phylogeographic Unit. PLoS ONE; 2015; 10, e0137843. [DOI: https://dx.doi.org/10.1371/journal.pone.0137843] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26372558]
53. Arruda, P.S.S.; Ferreira, D.C.; Oliveira, C.; Venere, P.C. DNA Barcoding Reveals High Levels of Divergence among Mitochondrial Lineages of Brycon (Characiformes, Bryconidae). Genes; 2019; 10, 639. [DOI: https://dx.doi.org/10.3390/genes10090639] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31450860]
54. Oliveira, C.; Avelino, G.S.; Abe, K.T.; Mariguela, T.C.; Benine, R.C.; Ortí, G.; Vari, R.P.; e Castro, R.M.C. Phylogenetic relationships within the speciose family Characidae (Teleostei: Ostariophysi: Characiformes) based on multilocus analysis and extensive ingroup sampling. BMC Evol. Biol.; 2011; 11, 275. [DOI: https://dx.doi.org/10.1186/1471-2148-11-275] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21943181]
55. Alvarez, F.; Cortinas, M.N.; Musto, H. The Analysis of Protein Coding Genes Suggests Monophyly ofTrypanosoma. Mol. Phylogenet. Evol.; 1996; 5, pp. 333-343. [DOI: https://dx.doi.org/10.1006/mpev.1996.0028]
56. Han, J.-H.; Cho, M.-H.; Kim, S.B. Ribosomal and protein coding gene based multigene phylogeny on the family Streptomycetaceae. Syst. Appl. Microbiol.; 2012; 35, pp. 1-6. [DOI: https://dx.doi.org/10.1016/j.syapm.2011.08.007]
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
1 The Co-Innovation Center for Sustainable Forestry in Southern China, College of Life Sciences, Nanjing Forestry University, Nanjing 210037, China;
2 College of Animal Science and Technology, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China;